Browse SoTA > Methodology > Computed Tomography (CT)

Computed Tomography (CT)

57 papers with code · Methodology

The term “computed tomography”, or CT, refers to a computerized x-ray imaging procedure in which a narrow beam of x-rays is aimed at a patient and quickly rotated around the body, producing signals that are processed by the machine's computer to generate cross-sectional images—or “slices”—of the body.

( Image credit: Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector )

Benchmarks

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Greatest papers with code

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

12 Aug 2019facebookresearch/maskrcnn-benchmark

When reading medical images such as a computed tomography (CT) scan, radiologists generally search across the image to find lesions, characterize and measure them, and then describe them in the radiological report.

COMPUTED TOMOGRAPHY (CT)

Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels

5 Jun 2019fizyr/keras-retinanet

We propose a highly accurate and efficient one-stage lesion detector, by re-designing a RetinaNet to meet the particular challenges in medical imaging.

COMPUTED TOMOGRAPHY (CT) REGION PROPOSAL SKIN LESION IDENTIFICATION

COVID-CT-Dataset: A CT Scan Dataset about COVID-19

30 Mar 2020UCSD-AI4H/COVID-CT

Using this dataset, we develop diagnosis methods based on multi-task learning and self-supervised learning, that achieve an F1 of 0. 90, an AUC of 0. 98, and an accuracy of 0. 89.

COMPUTED TOMOGRAPHY (CT) COVID-19 DIAGNOSIS MULTI-TASK LEARNING SELF-SUPERVISED LEARNING

A Reference Architecture for Plausible Threat Image Projection (TIP) Within 3D X-ray Computed Tomography Volumes

15 Jan 2020ljvmiranda921/pyswarms

Threat Image Projection (TIP) is a technique used in X-ray security baggage screening systems that superimposes a threat object signature onto a benign X-ray baggage image in a plausible and realistic manner.

COMPUTED TOMOGRAPHY (CT)

ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

3 Aug 2019JunMa11/MICCAI-OpenSourcePapers

Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training.

COMPUTED TOMOGRAPHY (CT) IMAGE-TO-IMAGE TRANSLATION MEDICAL IMAGE GENERATION METAL ARTIFACT REDUCTION

The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

31 Mar 2019neheller/kits19

The morphometry of a kidney tumor revealed by contrast-enhanced Computed Tomography (CT) imaging is an important factor in clinical decision making surrounding the lesion's diagnosis and treatment.

COMPUTED TOMOGRAPHY (CT) DECISION MAKING TUMOR SEGMENTATION

Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Images

22 Apr 2020HzFu/COVID19_imaging_AI_paper_list

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis.

CAMOUFLAGED OBJECT SEGMENTATION CAMOUFLAGE SEGMENTATION COMPUTED TOMOGRAPHY (CT)

Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT

20 Jun 2018simontomaskarlsson/GAN-MRI

Here, we evaluate two unsupervised GAN models (CycleGAN and UNIT) for image-to-image translation of T1- and T2-weighted MR images, by comparing generated synthetic MR images to ground truth images.

COMPUTED TOMOGRAPHY (CT) IMAGE-TO-IMAGE TRANSLATION MEDICAL IMAGE GENERATION